 Hello everyone, welcome to theCUBE's coverage of High Performance 2023, covering everything HPC, machine learning, AI, high performance analytics and quantum computing. Part of the ISC 2023, CUBE event coverage. The segment today is Quantum Computing, next hardware accelerations right around the corner. It's the next, next gen coming. Got two great guests here on the power panel, Burns Healy, Emerging Technology Researcher with Dell Research Office, and Mike Robolard, Senior Distinguished Engineer with Dell. Gentlemen, thank you for joining me on this quantum computing topic. Yeah, thank you for having us, Tom, we appreciate it. So we love, we love high performance, super computing, super cloud, super apps. The market's totally primed for this big wave coming and quantum's right around the corner. Some of the smartest people or engineers are working on quantum. It's quite the buzz and it's legit. It's a whole other paradigm shift. HPC professionals and customers, they're smart and they're into hardware. They're into all super computing, but they're just now putting their toe in the water with quantum, but they're very aligned with the concept. So let's start with kind of just setting the table. Can you guys describe what quantum computing is in a way that a regular HPC guru or professional can understand and how it's different and what are the advantages are going to be? Yeah, I'd say that the best mental model for quantum as it would serve an HPC expert, HPC customer, somebody interested in HPC, will be to think of it as another kind of hardware accelerator. So if you go back and you think about GPUs, right? Of course, GPUs were originally designed for graphics. Now we're finding applications for them in AIML training, say large language models, other kinds of workloads like that. And there are specific workloads that you see that run better on GPUs and then other workloads for which they don't really provide an advantage. And I would encourage everybody to have that same thought process in terms of quantum. So there are going to be particular classes of workloads that quantum technologies are going to have the capability to accelerate and really improve over our current methods of processing those workloads. And then there are others that they won't. So it'll be just a journey of as the technology matures, identifying those places where we can get an advantage and trying to continually leverage more and better quantum techniques to expand that world. I mean, I like the GPU example because I think people can relate to that. I remember when GPUs came, oh, GPUs, graphics accelerator, it's a bolt-on, it's a hardware assist specific use case, had a beach head, had one use case. Now it's everything, machine learning, similar scope with quantum. It's going to land on some use cases. What are some of those things that you see popping out right out of the gate? Yeah, no. So the big one that of course captures a lot of attention is when people say that quantum computers are going to break encryption and it's going to be fundamentally a lawless world where every possible message is now interceptable and decryptable by any actor with an internet connection. And what is true is that our current encryption standard, which is RSA with a specific length key, is susceptible to a faster brute force attack via a quantum computer. But it's very specific to that particular encryption scheme, to that RSA encryption method. So in that realm, RSA is one particular workload. If you're talking about decryption, that quantum computers could be advantageous at, but other encryption methods are not susceptible to that same kind of attack. So even within domain, I think identifying those particular workloads that quantum is helpful for is a bit of a fine line. So encryption, decryption, as well as things like quantum machine learning are coming online. That's just like all technology evolutions, the previous generation is not as good as the next one. And if you don't move to the next one, I mean, look at the, everyone's doing two-factor authentication, people are like, that's crazy. A decade ago, no one did that, right? I mean, well, some people did, I did, but that's the point. And so I think one of the other things that's pretty universal is this idea of optimization and every company is always trying to optimize their business operations. And quantum computers appear to be very well-suited for optimization types of problems. So there are a lot of applications. It's just a question to go into finding them. Michael, that's a great point. And I like the next question I wanted to ask you guys is so many quantum technologies out there, quantum community technologies. What's the map look like? And what do you look for in a company while working in the area that impresses you? What's some of the map of the landscape look like out there in this market for companies? What's, who's innovating? What does success look like right now? I mean, I'd say everybody's innovating. What's so beautiful about being so early on in the maturation of this technology is we've got a lot of different paths. Every company has their own roadmap for scaling up if they're a hardware company, scaling up to additional qubits, which are the fundamental unit of quantum computing, or if they're an algorithm development company, they've got all of these different areas that they want to try and tackle. And so I see all of these ambitious, really excited technologists going after this. And I think there's a lot up and down the stack, a lot to be excited about. I'd say, yeah. What's the landscape point of view like? Are people sharing? I mean, open source, for example, everyone's sharing content. What is the landscape of the companies look like that impress you? What's the company landscape like? Like what capabilities? And so we're not going to be picking winners at this point, right around this interview. But when you see companies that understand the physics, when you see companies that are able to connect to user needs, to user workloads, when you see companies that are taking and advancing the engineering or building these systems, right? That's a great quantum company. And there are a few examples of that in the space. And you asked a second question around how competitive are these companies? It's an interesting time, right? Because there's cooperation, but there's also competition. And you've got multiple threads of research and development that are relatively independent, all kind of progressing independently. And at this point, it's really too early to call. Yeah, and it reminds me of we're just, we're talking a lot about AI and other segments around ISC and HPC and how AI is just exploded because of the compute and large scale cloud and data models that are out there, which is a current situation. That's what's happening now. That wasn't available years ago. So when things just explode, they just go exponential. What kind of problems does a quantum address in the HPC world, what are we looking for for that pivot point, that kick up? What needs to happen? What do you guys envision the sequence? Because I'm imagining that quantum is just gonna, it's gonna continue to advance. People are gonna collaborate. Co-operations gonna happen. But there's gonna be a couple of bits that have to flip. Yes, yes. Can you share your vision on that? Because I think that's really fascinating. Absolutely. And one thing that I think it is helpful to remember is that when we say quantum technologies, right? It actually encompasses a whole lot of different kinds of architectures. So in our experience right now, there's kind of two main competing standards or not even competing standards, but complimentary standards for what a quantum computer does. So there is a kind of universal gate-based QPU machine. So these are the kinds of machines that you've probably more heard about in terms of what's available in the literature out there. But also in addition to those kind of universal processors, there's a very specialized kind of processor called a quantum annealer. And the quantum annealer uses different parts of quantum mechanics to do computations. And this is what Mike was getting at when he said optimization is a very hot topic and a very, you know, is an area in which we'd expect to see a quantum, at least provide some kind of advantage, hopefully in the near future. And these are the kinds of problems that are your sort of large enterprise scale, large search-based problems that you want to optimize revenue or you want to optimize time or resource allocation. And that's one place I'm excited to see coming online soon because there are quantum annealers that are beginning to scale. And I think as we get the chance to explore our current optimization problems on those technologies, I think we'll see where that fits in. Michael, what's your take? Renaissance and computes here. I mean, it's just more headroom all around. Yeah, and I just want to, you know, focus in a bit on the second part of your question there, the, you know, is it better than classical HPC? What are the differences there? And, you know, I think we're going to see an evolution of, you know, what we think HPC is, much like we saw in evolution, there was a time before HPC had GPUs and that was fine, right? And today it has GPUs and that's even better. And there will be a future where it will be augmented. And I think the only question is how much? And, you know, I think that's the exciting part. So, you know, I'm looking at some of the comments online around orchestration, intelligent orchestration, quantum being another tool in the HPC arsenal. This is a really key point, getting that orchestration of resources is very key. How do you guys react to that? What's that mean? Right, so I want to think of a workflow when you're talking about some large, you know, workload or some large job or some large sequence of jobs. And you imagine now, not only do you have possible accelerators in the form of a GPU, but you also have quantum processing units, QPUs, and you also have quantum annealers and you have other technologies that could provide advantage. And so before that, that decision was an easy one. Do I want to run this on a CPU? Do I want to run it on a GPU, right? And now you have a much tougher question to answer, which is which pieces of these should be, of this workload should be allocated to which resources? And I think that's where the intelligent orchestration comes into place. So it's breaking down those jobs, identifying the different components of them and where they fit best in terms of what's going to advantage them, what kind of hardware architecture is going to match this workload best. And it's not just a matter of enhanced execution time, but you also have questions of accuracy, fidelity. You have availability of hardware, you have price of hardware. So all of these questions get rolled into one kind of final decision. And at the end of the day, that decision is being made in an HPC environment, right? The quantum computer is not doing the orchestration. That is still a classical machine running on hardware that we're all used to that is making those decisions and dispatching those parts of your workload. That's a great point. In fact, my next question was going to be in this event in the industry, the hallway conversations people are saying, HPC and quantum computing are both necessary to use a quantum computer working together. Can you explain what that means? Is it, do you agree with that statement and that's going on in the industry? And what does it mean? Yeah, I would absolutely agree with that. I think that we should see, as you mentioned, a tool in the HPC arsenal, quantum is another accelerator. You can't use a GPU without a CPU, right? Without a traditional computer behind it. It doesn't make sense. And the same thing is going to be true for quantum indefinitely because we're going to need to orchestrate those resources and see what makes sense. But especially in the near term, we're still in what we in the quantum landscape, like to call the noisy intermediate scale quantum or NISC era. And what that means is while these devices are impressive, they still are subject to a lot of stochasticity a lot of noise. You typically run a single workload many, many times in order to try and drown out that noise with the signal and recover some real meaning to your end result. And so as we remain in that NISC era, in addition to the orchestration, you have questions like pre-processing by classical infrastructure, post-processing by classical infrastructure. You might have to take an output and interpret it, using your classical hardware. So it's still the case, especially now, that the quantum is going to be able to do a piece of it, but it's going to be kind of sandwiched by these pre and post classical layers that are going to be needed to interpret what it is the quantum technology has given you. And just to add to that a little bit, we are always going to be wrapping quantum computers with classical electronics and classical machines. They really have a symbiotic relationship. And I think the way we should think about it is that quantum is going to augment classical and classical enables quantum. And so the ratios may change, where we run particular inner loops may change, but there are a few significant differences that mean both are incredibly important. I mean, today we have the ability to do 80 billion transistors in a device and we can do it at scale. We can make incredibly reliable devices and it only takes 24 transistors to build an adder as an example. In addition, it will be done with classical machines, right? There are other use cases, other applications, other things that we'll do for quantum. And we could break that down a little bit more, but I think the key takeaway here is these are symbiotic technologies. I agree, I agree with you 100%. If you look at the evolution of what's going on with large scale, just take the hyperscale and then the on-prem and edge that's developing. It's basically distributed computing. Okay, that's the distributed computing paradigm. That's going to be like a piece. I call it like the PC. Once a server is now the internet, right? So everything's distributed and you're starting to see the subsystems being more focused. The focus on silicon, the focus on chips, the focus on the connection points between them. So again, the GPU is a great example. So I could see quantum integrating in with HPC clearly as a beachhead and then from there, it's whatever track it takes. I mean, that's just evolution. That's just the computer industry. That's how it works. Yep, and it's very different than, you know, if you look at the earlier phases of compute where we had vacuum tubes replace mechanical systems and, you know, semi-conductors replace vacuum tubes, it's not going to be like that, right? There is no replacement, right? We will use semiconductors and, you know, if all goes according to plan, we will have quantum machines and they will be together. It's an operating system. It's all the same, it's the same theory. I love it. Anyway, I don't want to harp on that, but I want to get into some specific market questions. Some industry pundits are predicting a quantum winter. The hype cycles obviously is well into the development. Is the, are we in the tropic disillusionment? What do you guys think about this? What's the comment on this quote, quantum winter? Yes or no? I can't say anything about a quantum winter. I'm not unfortunately a weatherman, but I can say that we need to make sure that our messaging is clear from within, you know, the quantum industry. I think it's our responsibility to make sure that we're accurately representing the state of the technology and accurately representing what his capabilities are right now. I think roadmaps are great. And so far in my experience, companies have by and large lived up to those roadmaps. And I think that if you read the capabilities and you read the roadmaps and you understand what they're saying, you will be seeing that really by and large, we're trying to under promise rather than over promise. I think that there, I wouldn't foresee any kind of trough of disillusionment as long as we are understanding where the state of play is and we're not allowing ourselves to get too far ahead of ourselves in terms of the timeline that we see the technology maturing at. I think the expectation setting is right on. I think that's key point. I mean, if you over play your hand here, the tech, the scale, you just talked about this earlier about the classical intersection with classical computing. Yeah, I think it's more of a journey. It's not about seasons, it's a journey. And there is work that we have to do. And as long as we're clear and understand that work, it will progress. So the reality settles in, people who work, it's not like the industry's not going backwards or at it's going forward. Always moving forward. So the question on quantum being practical, some are saying when it reach one million qubits, it's going to be decades before it reach a million. What do you think about that? Is that off base? How much faster can quantum scale vis-a-vis say the classical trajectory? Is there, can you get a feel for where we are in the progress? There is one particular aspect to this question that makes it both very difficult to answer, unfortunately, but also gives me a lot of hope and optimism. And so what's really particular about this is that there's so many different kinds of even when you zoom in on your gate-based traditional quantum computer, as you might think of it, even within that schema, there's a lot of different technologies, a lot of different hardware architectures that are achieving that outcome. So you have things like trapped ions, you have neutral atoms, you have photonics, even within the schema of manipulating a qubit and measuring it, which is fundamentally all that a QPU is doing, there's a lot of different ways in a physical sense to make that happen. And so all of these different technologies are advancing in parallel and already we're seeing some of them scale better. Some of them have better coherence times. Some of them are cheaper to manufacture or easier to maintain. And they've all got their own advantages and of course disadvantages. And what makes me optimistic is that all of these players in the field are gonna keep going, right? They're all gonna keep working on their technology going to try to scale it and going to try to achieve some kind of benchmark that they've set out for themselves. And what that benchmark is, whether it's a million qubits or it's not a million qubits, will depend on the technology too. One of the reasons one million qubits has been set out there as this kind of benchmark is because there's the idea that you're going to need surplus qubits than you really need in order to do that error correction. You're going to need what's called a logical qubit made up out of many physical qubits. And you may not need that or you may not need a thousand to one ratio if the fidelity of your qubits is really high. So it's difficult to predict but I'm really optimistic about the overall timeline just because there's this diversity, there's this growth in the industry and there's starting to be this really, really keen attention and investment paid to it. Yeah, man, it's a moonshot metric. I guess my final question to wrap up here is why should people start paying attention to quantum now and how HPC is integrated into it? This is where we're at now. How do I should I think about it? What steps do I take? What's in it for me? What's for the people in the industry? Why should people start paying attention to quantum now? So let me jump in here for just a moment. If we look around, right, there are plenty of impossible things all around us and those impossible things are the function of a large journey, right? Manufacturing, constant and engineering innovation, science, supply chain, right? And over long periods of time and quantum will be no different. And so what we need to be thinking about is how do we individually and as organizations add energy into this virtuous cycle? How do we make the flywheel go faster so that we can all benefit from the outcomes that are possible? And so there are folks whose responsibility will be to, as Byrne said, figure out error correction. That's a huge technical problem. Other folks are focusing on trying to train up a new generation of engineers to be able to use this technology. As businesses, we should be focusing on the applications that accelerate our businesses. And there are people such as yourself, John, that serve to facilitate the conversation, right? To build the connections between people so that we can all head towards this common goal. And so it's really, when we think about this, we need to think of a journey. We need to think of a flywheel. We need to figure out how we're going to add energy into this so that we can take the benefit. Byrne, your thoughts. Yeah, absolutely. I mean, one additional answer. So everything Mike said is absolutely correct. And we do want to see the industry moving forward. And that can only happen when people are thinking about the technology. And there's a lot of upskilling to do. There is going to be a little bit of a learning curve when it comes to quantum. Not because I think it'll be difficult to use per se, but because the kinds of quantum algorithms that we see that are going to provide us with advantage are counterintuitive. They're quantum mechanical nature. They utilize superposition. And it's just not a natural way for us to think. So I'd love to see developers and people in charge of optimizing given scenarios. I'd love to see them start to think about it now and start to wrap their heads around what is the capability of this technology. And it won't be that long until we see a piece of advantage where quantum is a portion of a larger heterogeneous compute environment. Well, I say we start teaching physics in first grade. Let's get that on the table right away. Okay, so that's number one. Because everyone's going to be coding anyway with no code, low code. Just get physics into the curriculum at first grade. Why don't we start with there? We are so enthusiastic. Mike, we are into quantum. We believe this is an evolution. And it's going to hit a tipping point. And we're going to continue to amplify the industry. We think quantum is positive for the industry and overall everyone in HPC. Super computing is being redefined. Super cloud is emerging and super apps are coming onto the scene with AI in there. All going to need computing. That's what we see clearly the next 20 years as a shift. And we really appreciate you guys doing what you do. And thanks for coming on this program. Just final word, put the plug in for Dell. What are you guys looking to do for collaboration? It's a community. People are looking to do deals, work together, share information, take the last minute guys and share your thoughts on what Dell's doing and what you guys are looking for. Absolutely. So when we say that quantum currently and probably always will or will always rely on that classical infrastructure layer, that's where we want to play. We want to play in this organization, orchestration, optimization layer where we can send the workloads to those appropriate resources and those appropriate accelerators and really be that orchestration piece where we are the first contact for a workload. We can break it down, do that optimization and orchestrate and allocate these resources as is appropriate for the best end result for the customer. Mike? Yeah, start by looking at Dell.com and the quantum computing page and reach out, there's some resources there. You can learn some things, you can meet some people and you can learn about the Dell quantum computing solution. So that would be my quick plug. HPC and quantum go better together and that's the direction. And thanks for coming on this program. What a great panel. Thanks for unpacking and discussing bringing the quantum conversation to the table. We really appreciate it. Thanks for having me, John. Okay, this is the cubes coverage of high performance 2023 part of ISC 2023 event coverage. I'm John Furrier, your host. Thanks for watching.